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pyg-team / pytorch_geometric

Graph Neural Network Library for PyTorch
https://pyg.org
MIT License
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Failure to run the C++ example of torch geometric (Aborted (Core Dumped)) #9750

Open wu-ys opened 2 weeks ago

wu-ys commented 2 weeks ago

🐛 Describe the bug

Hi all, I am trying to run the c++ example here. I have done all steps except running the final c++ program, which fails with Aborted (Core Dumped) when running the c++ loading function.

To be more specifically, when I remove the torch-geometric Modules from the model in save_mode.py, the c++ program will run smoothly without errors. So I think this is a problem regarding loading torch-geometric modules in c++.

I have checked the compilation and linking of Pytorch-sparse and Pytorch-scatter. Simple c++ test demos using features (e.g. the demo in #1718 and https://github.com/rusty1s/pytorch_scatter/issues/147) from the two libraries could run successfully. How can I handle this error?

Versions

PyTorch version: 2.3.0 Is debug build: False CUDA used to build PyTorch: 12.1 ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.6 LTS (x86_64) GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0 Clang version: Could not collect CMake version: version 3.22.0-rc1 Libc version: glibc-2.39

Python version: 3.10.14 (main, May 6 2024, 19:42:50) [GCC 11.2.0] (64-bit runtime) Python platform: Linux-5.4.0-190-generic-x86_64-with-glibc2.39 Is CUDA available: True CUDA runtime version: 12.4.131 CUDA_MODULE_LOADING set to: LAZY GPU models and configuration: GPU 0: NVIDIA A100 80GB PCIe Nvidia driver version: 550.54.15 cuDNN version: Could not collect HIP runtime version: N/A MIOpen runtime version: N/A Is XNNPACK available: True

Versions of relevant libraries: [pip3] numpy==1.26.4 [pip3] torch==2.3.0 [pip3] torch_cluster==1.6.3+pt23cu121 [pip3] torch_geometric==2.5.3 [pip3] torch_scatter==2.1.2+pt23cu121 [pip3] torch_sparse==0.6.18+pt23cu121 [pip3] torch_spline_conv==1.2.2+pt23cu121 [pip3] torchaudio==2.3.0 [pip3] torchinfo==1.8.0 [pip3] torchvision==0.18.0 [pip3] triton==2.3.0 [conda] blas 1.0 mkl
[conda] cuda-cudart 12.1.105 0 nvidia [conda] cuda-cupti 12.1.105 0 nvidia [conda] cuda-libraries 12.1.0 0 nvidia [conda] cuda-nvrtc 12.1.105 0 nvidia [conda] cuda-nvtx 12.1.105 0 nvidia [conda] cuda-opencl 12.4.127 0 nvidia [conda] cuda-runtime 12.1.0 0 nvidia [conda] ffmpeg 4.3 hf484d3e_0 pytorch [conda] libcublas 12.1.0.26 0 nvidia [conda] libcufft 11.0.2.4 0 nvidia [conda] libcurand 10.3.5.147 0 nvidia [conda] libcusolver 11.4.4.55 0 nvidia [conda] libcusparse 12.0.2.55 0 nvidia [conda] libjpeg-turbo 2.0.0 h9bf148f_0 pytorch [conda] libnvjitlink 12.1.105 0 nvidia [conda] mkl 2023.1.0 h213fc3f_46344
[conda] mkl-service 2.4.0 py310h5eee18b_1
[conda] mkl_fft 1.3.8 py310h5eee18b_0
[conda] mkl_random 1.2.4 py310hdb19cb5_0
[conda] numpy 1.26.4 py310h5f9d8c6_0
[conda] numpy-base 1.26.4 py310hb5e798b_0
[conda] pytorch 2.3.0 py3.10_cuda12.1_cudnn8.9.2_0 pytorch [conda] pytorch-cuda 12.1 ha16c6d3_5 pytorch [conda] pytorch-mutex 1.0 cuda pytorch [conda] torch-cluster 1.6.3+pt23cu121 pypi_0 pypi [conda] torch-geometric 2.5.3 pypi_0 pypi [conda] torch-scatter 2.1.2+pt23cu121 pypi_0 pypi [conda] torch-sparse 0.6.18+pt23cu121 pypi_0 pypi [conda] torch-spline-conv 1.2.2+pt23cu121 pypi_0 pypi [conda] torchaudio 2.3.0 py310_cu121 pytorch [conda] torchinfo 1.8.0 pypi_0 pypi [conda] torchtriton 2.3.0 py310 pytorch [conda] torchvision 0.18.0 py310_cu121 pytorch

AyushmanGarg commented 1 week ago

@akihironitta can I be assigned this bug?